DTA_llama2_13b

Model Description

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DTA_llama2_7b is from the paper "Divide-Then-Aggregate: An Efficient Tool Learning Method via Parallel Tool Invocation". It is a large language model capable of invoking tools and can parallel invoke multiple tools within a single round. The tool format it used is similar to OpenAI's Function Call.

Uses

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The related code can be found in our GitHub repository.

Training Data

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The training data comes from our specially constructed DTA-Tool, which is derived from ToolBench.

Evaluation

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Testing Data

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We evaluated the performance of DTA-Llama on StableToolBench.

Results

Citation

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@misc{zhu2025dividethenaggregateefficienttoollearning,
      title={Divide-Then-Aggregate: An Efficient Tool Learning Method via Parallel Tool Invocation}, 
      author={Dongsheng Zhu and Weixian Shi and Zhengliang Shi and Zhaochun Ren and Shuaiqiang Wang and Lingyong Yan and Dawei Yin},
      year={2025},
      eprint={2501.12432},
      archivePrefix={arXiv},
      primaryClass={cs.LG},
      url={https://arxiv.org/abs/2501.12432}, 
}